Marc works on both openlayers and GeoExt. Openlayers is a javascript library with lots and
lots of features.

To see what it can do, look at the 161 examples on the website :-) It works
with both vector layers and raster layers.

Openlayers is a quite mature project, the first version is from 2006. It
changed a lot to keep up with the state of the art. But they did take care to
keep everything backwards compatible. Upgrading from 2.0 to 2.2 should have
been relatively easy. The 4.0.0 version came out last month.

Openlayers...

Allows many different data sources and layer types.

Has build-in interaction and controls.

Is very actively developed.

Is well documented and has lots of examples.

The aim is to be easy to start with, but also to allow full control of your
map and all sorts of customization.

Geoserver is a java-based server for geographical
data. It support lots of OGC standards (WMS, WFS, WPS, etc). Flexible,
extensible, well documented. “Geoserver is a glorious example that you can
write very performant software in java”.

Geoserver can connect to many different data sources and make those sources
available as map data.

If you’re a government agency, you’re required to make INSPIRE metadata
available for your maps: geoserver can help you with that.

A big advantage of geoserver: it has a browser-based interface for configuring
it. You can do 99% of your configuration work in the browser. For maintaining:
there is monitoring to keep an eye on it.

Something to look at: the importer plugin. With
it you get a REST API to upload shapes, for instance.

The latest version also supports LDAP groups. LDAP was already supported, but
group membership not yet.

Dominik is one of the MapProxy developers. Mapproxy
is a WMS cache and tile cache. The original goal was to make maps quicker by
caching maps.

Some possible sources: WMS, WMTS, tiles (google/bing/etc), MapServer. The
output can be WMS, WMS-C, WMTS, TMS, KML. So the input could be google maps
and the output WMS. One of their customers combines the output of five
different regional organisations into one WMS layer...

The maps that mapproxy returns can be stored on a local disk in order to
improve performance. They way they store it allows mapproxy to support
intermediary zoom levels instead of fixed ones.

The cache can be in various formats: MBTiles, sqlite, couchdb, riak, arcgis
compact cache, redis, s3. The cache is efficient by combining
layers and by omitting unneeded data (empty tiles).

You can pre-fill the cache (“seeding”).

Some other possibilities, apart from caching:

A nice feature: clipping. You can limit a source map to a specific area.

Reprojecting from one coordinate system to another. Very handy if someone
else doesn’t want to support the coordinate system that you need.

WMS feature info: you can just pass it on to the backend system, but you can
also intercept and change it.

QGis is an opern source gis platform. Desktop, server,
browser, mobile. And it is a library. It runs on osx, linux, windows,
android. The base is the QT ui library, hence the name.

Qgis contains almost everything you’d expect from a GIS packages. You can
extend it with plugins.

Qgis is a very, very active project. Almost 1 million lines of code. 30.000+
github commits. 332
developers have worked on it, in the last 12 months 104.

Support via documentation, mailinglists and http://gis.stackexchange.com/ . In
case you’re wondering about the names of the releases: they come from the
towns where the twice-a-year project meeting takes place :-)

You can choose a layout and fill in and configure the various parts. Layers
you want to show: add sources. You can configure security/access with roles.

An example component: a search form for addresses that looks up addresses with
sql or a web service. Such a search form can be a popup or you can put it in
the sidebar, for instance. CSS can be customized.

The postnas project is a solution for importing ALKIS
data,
a data exchange format for the german cadastre (Deutsch: Kataster).

PostNAS is an extension of the GDAL library for the “NAS” vector data
format. (NAS = normalisierte Austausch Schnittstelle, “normalized exchange
format”). This way, you can use all of the gdal functionality with the
cadastre data. But that’s not the only thing: there’s also a qgis
plugin. There is configuration and conversion scripts for postgis, mapbender,
mapserver, etc.

They needed postprocessing/conversion scripts to get useful database tables
out of the original data, tables that are usable for showing in QGis, for instance.

So... basically a complete open source environment for working with the
cadastre data!